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EVAL6_CARLA_DETECTION.mk
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EVAL6_CARLA_DETECTION.mk
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# Download and extract dataset of carla_over_obj_det
CARLA_OVERHEAD_DATASET = $(DATASETS)/carla_over_obj_det/train/kwcoco_annotations_all.json $(DATASETS)/carla_over_obj_det/val/kwcoco_annotations_all.json
$(CARLA_OVERHEAD_DATASET):
> $(error Missing dataset)
%/eval6_dev_benign/test_prediction.json: %/.hydra/config.yaml %/.hydra/hydra.yaml %/checkpoints/last.ckpt
> $(MART) task_name=$(shell $(YQ) .task_name < $*/.hydra/config.yaml) \
experiment=$(shell $(YQ) .hydra.runtime.choices.experiment < $*/.hydra/hydra.yaml) \
resume=$*/checkpoints/last.ckpt \
fit=false test=true \
hydra.run.dir=$(@D) \
datamodule.test_dataset.root=$(DATASETS)/carla_over_obj_det/dev \
datamodule.test_dataset.annFile=$(DATASETS)/carla_over_obj_det/dev/kwcoco_annotations.json \
datamodule.ims_per_batch=1
%/eval6_test_benign/test_prediction.json: %/.hydra/config.yaml %/.hydra/hydra.yaml %/checkpoints/last.ckpt
> $(MART) task_name=$(shell $(YQ) .task_name < $*/.hydra/config.yaml) \
experiment=$(shell $(YQ) .hydra.runtime.choices.experiment < $*/.hydra/hydra.yaml) \
resume=$*/checkpoints/last.ckpt \
fit=false test=true \
hydra.run.dir=$(@D) \
datamodule.test_dataset.root=$(DATASETS)/carla_over_obj_det/test \
datamodule.test_dataset.annFile=$(DATASETS)/carla_over_obj_det/test/kwcoco_annotations.json \
datamodule.ims_per_batch=1
.PHONY: carla_over_train
carla_over_train: ArmoryCarlaOverObjDet_TorchvisionFasterRCNN ## Train Faster R-CNN with the CarlaOverObjDet dataset from Armory.
.PHONY: ArmoryCarlaOverObjDet_TorchvisionFasterRCNN
ArmoryCarlaOverObjDet_TorchvisionFasterRCNN: .venv $(CARLA_OVERHEAD_DATASET) ## Train Faster R-CNN on truncated annotations but validation and test on all annotations
> $(MART) experiment=ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN \
task_name=$@ \
"datamodule.train_dataset.annFile=$$\{paths.data_dir\}/carla_over_obj_det/train/kwcoco_annotations.json"
.PHONY: carla_over_train_all
carla_over_train_all: ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN ## Train Faster R-CNN with the CarlaOverObjDet dataset from Armory.
.PHONY: ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN
ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN: .venv $(CARLA_OVERHEAD_DATASET) ## Train Faster R-CNN on all annotations and validate and test on all annotations
> $(MART) experiment=ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN \
task_name=$@ \
"+model.modules.losses_and_detections.model.model.trainable_backbone_layers=5" \
"+model.modules.losses_and_detections.model.model.min_size=960" \
"+model.modules.losses_and_detections.model.model.max_size=1280"
.PHONY: ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN_betteranchors
ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN_betteranchors: .venv $(CARLA_OVERHEAD_DATASET) ## Train Faster R-CNN with better anchors on all annotations and validate and test on all annotations
> $(MART) experiment=ArmoryCarlaOverObjDetAll_TorchvisionFasterRCNN \
task_name=$@ \
model=torchvision_faster_rcnn_better_anchors \
"+model.modules.losses_and_detections.model.model.trainable_backbone_layers=5" \
"+model.modules.losses_and_detections.model.model.min_size=960" \
"+model.modules.losses_and_detections.model.model.max_size=1280"
# modular faster rcnn implementation should be similar to torchvision
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN
ArmoryCarlaOverObjDetAll_FasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@
# train no layers
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_trainable0
ArmoryCarlaOverObjDetAll_FasterRCNN_trainable0: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.backbone.trainable_layers=0
# train 1 layer
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_trainable1
ArmoryCarlaOverObjDetAll_FasterRCNN_trainable1: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.backbone.trainable_layers=1
# train 2 layers
ArmoryCarlaOverObjDetAll_FasterRCNN_trainable2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.backbone.trainable_layers=2
# train 3 layers
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_trainable3
ArmoryCarlaOverObjDetAll_FasterRCNN_trainable3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.backbone.trainable_layers=3
# train 4 layers
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_trainable4
ArmoryCarlaOverObjDetAll_FasterRCNN_trainable4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.backbone.trainable_layers=4
# better anchors
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
model.modules.rpn.head.num_anchors=9 \
+model.modules.rpn.anchor_generator._convert_=partial \
"model.modules.rpn.anchor_generator.sizes.0=[0, 4, 16]" \
"model.modules.rpn.anchor_generator.sizes.1=[0, 8, 32]" \
"model.modules.rpn.anchor_generator.sizes.2=[4, 16, 64]" \
"model.modules.rpn.anchor_generator.sizes.3=[8, 32, 128]" \
"model.modules.rpn.anchor_generator.sizes.4=[128, 256, 512]"
.PHONY: ArmoryCarlaOverObjDetAll_ModularFasterRCNN
ArmoryCarlaOverObjDetAll_ModularFasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_ModularFasterRCNN \
task_name=$@
# smaller anchors
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors2
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors2_longer
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors2_longer: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
trainer.max_steps=$(shell python -c "import math; print(math.ceil(3600/2 * 12))")
# smaller anchors
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors3
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64, 128]"
# even smaller anchors
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[4, 8, 16, 32, 64]"
# even smaller anchors with 1/2 learning rate
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4_lr0.00625
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4_lr0.00625: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[4, 8, 16, 32, 64]"
model.optimizer.lr=0.00625
# even smaller anchors with 1/4 learning rate
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4_lr0.003125
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors4_lr0.003125: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[4, 8, 16, 32, 64]"
model.optimizer.lr=0.003125
# smaller anchors with no last-level max pool
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors5
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors5: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null
# even smaller anchors with no last-level max pool
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors6
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors6: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64]" \
model.modules.backbone.extra_blocks=null
# smaller anchors with removed layer4 and last-level max pool
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors7
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors7: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]" \
model.modules.backbone.extra_blocks=null
# smaller anchors with smaller representation
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors8
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors8: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
model.modules.backbone.out_channels=128 \
model.modules.rpn.head.in_channels=128 \
model.modules.box_head.box_head.in_channels=$(shell python -c "print(128*7**2)")
# smaller anchors with roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors9
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors9: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
model.modules.box_head.box_roi_pool.aligned=true
# Remove layer4 but keep last-level max pool on layer3
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]"
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10_lr0.00625
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10_lr0.00625: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]" \
model.optimizer.lr=0.00625
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10_lr0.01
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors10_lr0.01: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]" \
model.optimizer.lr=0.01
# smaller anchors with removed layer4 and last-level max pool and roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors11
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors11: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
# smaller anchors with no last-level max pool and roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_lr0.00625
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_lr0.00625: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.optimizer.lr=0.00625
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
# Remove layer4 but keep last-level max pool on layer3 and roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors13
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors13: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"~model.modules.backbone.return_layers.layer4" \
"model.modules.backbone.in_channels_list=[256, 512, 1024]" \
model.modules.box_head.box_roi_pool.aligned=true
# even smaller anchors with no last-level max pool and roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_scratch
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_scratch: .venv
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.backbone.backbone.weights=false \
model.modules.backbone.backbone.norm_layer.path=mart.nn.nn.GroupNorm32 \
model.optimizer.lr=0.01 \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(3600/32 * 6))") \
datamodule.ims_per_batch=32 \
datamodule.world_size=4
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_scratch_longer
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors12_scratch_longer: .venv
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.backbone.backbone.weights=false \
model.modules.backbone.backbone.norm_layer.path=mart.nn.nn.GroupNorm32 \
model.optimizer.lr=0.075 \
model.optimizer.weight_decay=0 \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(3600/32 * 120))") \
datamodule.ims_per_batch=32 \
datamodule.world_size=4
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14_scratch
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14_scratch: .venv
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.backbone.backbone.weights=false \
model.modules.backbone.backbone.norm_layer.path=mart.nn.nn.GroupNorm32 \
model.optimizer.lr=0.05 \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(3600/32 * 6))") \
datamodule.ims_per_batch=32 \
datamodule.world_size=4
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14_scratch_longer
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors14_scratch_longer: .venv
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.backbone.backbone.weights=false \
model.modules.backbone.backbone.norm_layer.path=mart.nn.nn.GroupNorm32 \
model.optimizer.lr=0.075 \
model.optimizer.weight_decay=0 \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(3600/32 * 120))") \
datamodule.ims_per_batch=32 \
datamodule.world_size=4
# smaller anchors w/ roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors15
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors15: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[8, 16, 32, 64, 128]" \
model.modules.box_head.box_roi_pool.aligned=true
# even smaller anchors w/ roialignv2
.PHONY: ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors16
ArmoryCarlaOverObjDetAll_FasterRCNN_betteranchors16: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"model.modules.rpn.anchor_generator.sizes=[4, 8, 16, 32, 64]" \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllDepth_FasterRCNN
ArmoryCarlaOverObjDetAllDepth_FasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[depth]" \
"datamodule.val_dataset.modalities=[depth]" \
"datamodule.test_dataset.modalities=[depth]" \
"model.modules.preprocessor.image_mean=[127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[74.119, 2.4791, 68.022]"
.PHONY: ArmoryCarlaOverObjDetAllDepth_FasterRCNN_2
ArmoryCarlaOverObjDetAllDepth_FasterRCNN_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[depth]" \
"datamodule.val_dataset.modalities=[depth]" \
"datamodule.test_dataset.modalities=[depth]" \
"model.modules.preprocessor.image_mean=[127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAllDepth_FasterRCNN_3
ArmoryCarlaOverObjDetAllDepth_FasterRCNN_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[depth]" \
"datamodule.val_dataset.modalities=[depth]" \
"datamodule.test_dataset.modalities=[depth]" \
"model.modules.preprocessor.image_mean=[127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAllDepth_FasterRCNN_4
ArmoryCarlaOverObjDetAllDepth_FasterRCNN_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[depth]" \
"datamodule.val_dataset.modalities=[depth]" \
"datamodule.test_dataset.modalities=[depth]" \
"model.modules.preprocessor.image_mean=[127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAll1Depth_FasterRCNN
ArmoryCarlaOverObjDetAll1Depth_FasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[31.468]" \
"model.modules.preprocessor.image_std=[9.5084]"
.PHONY: ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_2
ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[31.468]" \
"model.modules.preprocessor.image_std=[9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_3
ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[31.468]" \
"model.modules.preprocessor.image_std=[9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_4
ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[31.468]" \
"model.modules.preprocessor.image_std=[9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_5
ArmoryCarlaOverObjDetAll1Depth_FasterRCNN_5: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"+model.modules.backbone.channel_slice=[3, 4]" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=6" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_2
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=6" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_3
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=6" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_4
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=6" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=4" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_2
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=4" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_3
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=4" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_4
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_1depth_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.backbone.backbone.in_channels=4" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_ModularFasterRCNN
ArmoryCarlaOverObjDetAllMultiModal_ModularFasterRCNN: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_ModularFasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.train_dataset.transforms.transforms.3.lambd.scale=255" \
"+datamodule.train_dataset.transforms.transforms.3.lambd.far=1" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.transforms.transforms.2.lambd.scale=255" \
"+datamodule.val_dataset.transforms.transforms.2.lambd.far=1" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.transforms.transforms.2.lambd.scale=255" \
"+datamodule.test_dataset.transforms.transforms.2.lambd.far=1" \
"model.modules.losses_and_detections.backbone.backbone.in_channels=4" \
"model.modules.losses_and_detections.preprocessor.image_mean=[0.485, 0.456, 0.406, 0.031468]" \
"model.modules.losses_and_detections.preprocessor.image_std=[0.229, 0.224, 0.225, 0.0095084]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.box_head_aux.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_2
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_3
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_4
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
model.modules.backbone.rpn.backbone.in_channels=3 \
"model.modules.backbone.rpn.channel_slice=[3, 6]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.box_head_aux.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_2
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_2: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
model.modules.backbone.rpn.backbone.in_channels=3 \
"model.modules.backbone.rpn.channel_slice=[3, 6]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_3
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_3: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
model.modules.backbone.rpn.backbone.in_channels=3 \
"model.modules.backbone.rpn.channel_slice=[3, 6]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128, 256]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128, 256]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_4
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_Semantic3Depth_4: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
model.modules.backbone.rpn.backbone.in_channels=3 \
"model.modules.backbone.rpn.channel_slice=[3, 6]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 127.86, 107.73, 7.6331]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 74.119, 2.4791, 68.022]"
.PHONY: ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_InverseSemantic
ArmoryCarlaOverObjDetAllMultiModal_FasterRCNN_InverseSemantic: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.backbone.rpn.channel_slice=[0, 3]" \
model.modules.backbone.rpn.backbone.in_channels=3 \
model.modules.backbone.rpn.extra_blocks=null \
"model.modules.backbone.box.channel_slice=[3, 4]" \
model.modules.backbone.box.backbone.in_channels=1 \
model.modules.backbone.box.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.box_head_aux.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllTrainValMultiModal_FasterRCNN_Semantic
ArmoryCarlaOverObjDetAllTrainValMultiModal_FasterRCNN_Semantic: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(4800/2 * 96))") \
"datamodule.train_dataset.root=$$\{paths.data_dir\}/carla_over_obj_det/train_val" \
"datamodule.train_dataset.annFile=$$\{paths.data_dir\}/carla_over_obj_det/train_val/kwcoco_annotations_all_iscrowd0.json" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.box_head_aux.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllTrainValDevMultiModal_FasterRCNN_Semantic
ArmoryCarlaOverObjDetAllTrainValDevMultiModal_FasterRCNN_Semantic: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN_Semantic \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(4820/2 * 96))") \
"datamodule.train_dataset.root=$$\{paths.data_dir\}/carla_over_obj_det/train_val_dev" \
"datamodule.train_dataset.annFile=$$\{paths.data_dir\}/carla_over_obj_det/train_val_dev/kwcoco_annotations_all_iscrowd0.json" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
"model.modules.rpn_aux.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.rpn.extra_blocks=null \
model.modules.backbone.box.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true \
model.modules.box_head_aux.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllTrainVal1Depth_FasterRCNN_5
ArmoryCarlaOverObjDetAllTrainVal1Depth_FasterRCNN_5: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(4800/2 * 96))") \
"datamodule.train_dataset.root=$$\{paths.data_dir\}/carla_over_obj_det/train_val" \
"datamodule.train_dataset.annFile=$$\{paths.data_dir\}/carla_over_obj_det/train_val/kwcoco_annotations_all_iscrowd0.json" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"+model.modules.backbone.channel_slice=[3, 4]" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
.PHONY: ArmoryCarlaOverObjDetAllTrainValDev1Depth_FasterRCNN_5
ArmoryCarlaOverObjDetAllTrainValDev1Depth_FasterRCNN_5: .venv $(CARLA_OVERHEAD_DATASET)
> $(MART) experiment=ArmoryCarlaOverObjDetAll_FasterRCNN \
task_name=$@ \
"datamodule=armory_carla_over_objdet_depth" \
trainer.max_steps=$(shell python -c "import math; print(math.ceil(4820/2 * 96))") \
"datamodule.train_dataset.root=$$\{paths.data_dir\}/carla_over_obj_det/train_val_dev" \
"datamodule.train_dataset.annFile=$$\{paths.data_dir\}/carla_over_obj_det/train_val_dev/kwcoco_annotations_all_iscrowd0.json" \
"datamodule.train_dataset.modalities=[rgb, depth]" \
"datamodule.val_dataset.modalities=[rgb, depth]" \
"datamodule.test_dataset.modalities=[rgb, depth]" \
"+model.modules.backbone.channel_slice=[3, 4]" \
"model.modules.backbone.backbone.in_channels=1" \
"model.modules.preprocessor.image_mean=[123.675, 116.28, 103.53, 31.468]" \
"model.modules.preprocessor.image_std=[58.395, 57.12, 57.375, 9.5084]" \
"model.modules.rpn.anchor_generator.sizes=[16, 32, 64, 128]" \
model.modules.backbone.extra_blocks=null \
model.modules.box_head.box_roi_pool.aligned=true
# We put yaml and pth into the folder $(MODEL_ZOO) so that Armory finds them.
.PRECIOUS: submission/%.yaml
submission/%.yaml: $(MODEL_ZOO)/%.yaml
> cp $< $@
.PRECIOUS: submission/%.pth
submission/%.pth: $(MODEL_ZOO)/%.pth
> cp $< $@
.PRECIOUS: submission/%.ckpt
submission/%.ckpt: $(MODEL_ZOO)/%.ckpt
> cp $< $@
# We will submit truncated YAMLs to run models in Armory, because
# 1. We only need the model definition at inference.
# 2. Variable interpolation in raw YAMLs may not work outside our MART-OSCAR environment.
# 3. We need to reset input_adv_* to NoAdversary anyway.
.PRECIOUS: $(MODEL_ZOO)/INTL_%.yaml
$(MODEL_ZOO)/INTL_%.yaml: logs/%/.hydra/config.yaml
> cat $< | $(YQ) '.model.modules.input_adv_training={"_target_": "mart.attack.NoAdversary"}' \
| $(YQ) '.model.modules.input_adv_validation={"_target_": "mart.attack.NoAdversary"}' \
| $(YQ) '.model.modules.input_adv_test={"_target_": "mart.attack.NoAdversary"}' \
| $(YQ) '{"_target_": .model._target_, "optimizer": null, "modules": .model.modules, "training_sequence": .model.training_sequence}' > $@
.PRECIOUS: $(MODEL_ZOO)/INTL_%.pth
$(MODEL_ZOO)/INTL_%.pth: logs/%/checkpoints/last.ckpt
> $(POETRY) run $(PYTHON) -c 'import torch; state_dict = torch.load("$<", map_location="cpu")["state_dict"]; torch.save(state_dict, "$@")'
logs/%/.hydra/config.yaml:
> $(error No configuration for model $* found! Create a symlink in logs via: ln -s <experiment>/<datetime> logs/$*")
logs/%/checkpoints/last.ckpt:
> $(error No checkpoint for model $* found! Create a symlink in logs via: ln -s <experiment>/<datetime> logs/$*")
# Always export batches
$(SCENARIOS)/carla_obj_det_%.json: $(ARMORY_SCENARIOS)/eval6/carla_overhead_object_detection/carla_obj_det_%.json
> cat $< | $(JQ) '.sysconfig.docker_image = "$(DOCKER_IMAGE_TAG_OSCAR)"' \
| $(JQ) '.scenario.export_batches = true' > $@
# Replace dataset with test dataset
$(SCENARIOS)/carla_obj_det_test_%.json: $(SCENARIOS)/carla_obj_det_%.json
> cat $< | ${JQ} '.dataset.name = "carla_over_obj_det_test"' \
| ${JQ} '.dataset.eval_split = "test"' > $@
$(SCENARIOS)/INTL_carla_over_obj_det_test_adversarialpatch_%.json: $(SCENARIOS)/carla_obj_det_test_adversarialpatch_undefended.json
> cat $< | $(JQ) 'del(.model)' \
| $(JQ) '.model.fit = false' \
| $(JQ) '.model.fit_kwargs = {}' \
| $(JQ) '.model.wrapper_kwargs = {}' \
| $(JQ) '.model.module = "oscar.models.art_estimator"' \
| $(JQ) '.model.name = "get_art_model"' \
| $(JQ) '.model.weights_file.checkpoint = "INTL_$*.pth"' \
| $(JQ) '.model.weights_file.config_yaml = "INTL_$*.yaml"' > $@
$(SCENARIOS)/INTL_carla_over_obj_det_test_multimodal_adversarialpatch_%.json: $(SCENARIOS)/carla_obj_det_test_multimodal_adversarialpatch_undefended.json
> cat $< | $(JQ) 'del(.model)' \
| $(JQ) '.model.fit = false' \
| $(JQ) '.model.fit_kwargs = {}' \
| $(JQ) '.model.wrapper_kwargs = {}' \
| $(JQ) '.model.module = "oscar.models.art_estimator"' \
| $(JQ) '.model.name = "get_art_model"' \
| $(JQ) '.model.weights_file.checkpoint = "INTL_$*.pth"' \
| $(JQ) '.model.weights_file.config_yaml = "INTL_$*.yaml"' > $@
submission/INTL_carla_over_obj_det_rgb_%.json: $(SCENARIOS)/INTL_carla_over_obj_det_test_adversarialpatch_%.json \
submission/INTL_%.pth \
submission/INTL_%.yaml
> cat $< | $(JQ) '.model.model_kwargs.modality = "rgb"' > $@
submission/INTL_carla_over_obj_det_depth_%.json: $(SCENARIOS)/INTL_carla_over_obj_det_test_multimodal_adversarialpatch_%.json \
submission/INTL_%.pth \
submission/INTL_%.yaml
> cat $< | $(JQ) '.model.model_kwargs.modality = "d"' > $@
submission/INTL_carla_over_obj_det_multimodal_%.json: $(SCENARIOS)/INTL_carla_over_obj_det_test_multimodal_adversarialpatch_%.json \
submission/INTL_%.pth \
submission/INTL_%.yaml
> cat $< | $(JQ) '.model.model_kwargs.modality = "rgbd"' > $@
submission/eval6_baseline_%.json: $(SCENARIOS)/%_test.json
> cp $< $@
.PHONY: results/Eval_%
results/Eval_%: submission/%.json
> ${ARMORY} run $< --no-docker --output-dir Eval_$*
results/EvalBenign_%: submission/%.json
> ${ARMORY} run $< --no-docker --skip-attack --output-dir EvalBenign_$*